code: def forward(self, x):
      x = F.relu(F.max_pool2d(self.conv1(x), 2))
      x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
      x = x.view(-1, 320)
      x = F.relu(self.fc1(x))
      x = F.dropout(x, training=self.training)
      x = self.fc2(x)
      return F.log_softmax(x, dim=0)
  
file_path: BentoML/examples/mlflow/pytorch/mnist.py
imports: import argparse
  import os
  import mlflow
  import mlflow.pytorch
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torchvision import datasets
  from torchvision import transforms
  import bentoml
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: F